Results for “runs”

Runs project-specific commands defined in a justfile, a Make-inspired syntax supporting parameters, dependencies, and multi-language recipes.

Runs a complete testing pipeline covering full test suites, automated and manual tests, and logs execution metadata for the /evolve pipeline.

Regenerates a specific code layer (schemas, services, routes, hooks, ui) or all layers, then runs the corresponding validation checks.

Schedules and runs recurring commands or scripts using cron expressions, with support for intervals, retries, locking, and logging.

Runs a QA validation cycle followed by bugfix until all criteria pass clean, with automated verification and re-validation.

Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration.

Send personalized cold email sequences via Gmail (self-managed loop), track replies, schedule follow-ups, and route booked meetings to Calendly. Runs daily on cron schedule.

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)

Routes marketing questions to the right specialist skill, orchestrates multi-skill campaigns, and runs cross-functional marketing audits.

Runs a structured bug-fix pipeline that scouts, diagnoses, fixes, reviews, and finalizes code changes with optional quality re-verification.

Runs a structured five-round brainstorm to capture actors, features, scope, constraints, and business rules before writing a spec.

Runs three parallel reviewer agents over recent code changes, aggregates their findings, and applies the fixes worth applying.

Runs a structured bug-fix pipeline: scouts evidence, diagnoses root cause, applies minimal fixes, and reviews before committing.

Launches long-running evaluation batches in isolated tmux sessions with pre-flight verification, monitoring, and post-flight analysis for unattended runs.

Runs focused experiments to validate feasibility of an idea, saving artifacts to .planning/spikes/ and supporting both idea and frontier modes.

Runs independent AI CLI reviewers over phase plans and merges their feedback into a REVIEWS.md file.

Configures and runs static analysis and linting tools across multiple languages, integrating with CI/CD and security platforms.

Forwards a Gmail message to new recipients, with options for body notes, attachments, CC/BCC, HTML formatting, drafts, and dry runs.

Routes research requests to appropriate modes and runs multi-agent deep research with evidence chains, plus optional monitoring.

Interact with GitHub issues, pull requests, Actions runs, and the GitHub API using the `gh` CLI.

Runs an interactive command in a separate window and waits for it to close. Invoked only when another skill explicitly calls for it, never on its own.

Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration.

Build work collaboratively in reviewable pieces, handing each piece back for review before starting the next, so the person stays in the lead and steers while the work happens instead of reviewing a finished result. Use when someone says to pair with them on something, asks to collaborate rather than direct, wants to review as it goes, or wants to guide the work piece by piece — on code, on a design decision, or on writing. For a test-first build it runs tdd, for restructuring it runs refactor, for an interface contract it runs design-an-api, and for plan work it runs iterative-plan-review or plan-implementation, each collaboratively; invoke any of those directly instead to run it straight through without pausing. Does not pace someone through code that already exists and builds nothing — use code-walkthrough. Does not explain, summarize, or research something instead of producing it — use code-overview or research.

Installs, deploys, runs, validates, troubleshoots, and stops NVIDIA AI-Q Blueprint infrastructure for local or self-hosted servers.

Runs a Trailmark summary analysis on a codebase to auto-detect languages, count entry points, and list dependencies.

Runs MySQL queries from an AI coding agent using the mysql2 Node.js library, with setup instructions for npm and TypeScript.

Runs Apify cloud actors for structured web scraping and exports datasets to S3, with input schema validation and webhook notifications.

Runs Google's Gemini CLI in one-shot mode with a positional prompt, supporting model selection, JSON output, and extension management.

Runs AEO audits on deployed sites, applies targeted fixes, validates JSON-LD schema, generates llms.txt files, and monitors changes over time.

Runs regression evaluations comparing agent edits against human-approved golden projects, and registers new goldens after human approval.

Runs a post-batch analysis pipeline after an eval completes: verifies results, executes analysis scripts, refreshes dashboards, and writes a summary report.

Runs a disciplined debugging loop for hard bugs and performance regressions, covering reproduction, hypothesis testing, instrumentation, fixing, and regression testing.

Manages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.

Builds and runs Telegram, Twitter/X, and WhatsApp bots for automated posting, engagement, and content distribution across platforms.

Scrapes Danish job sites for new positions matching your profile. Deduplicates across runs. Triggers on: job scrape, find jobs, search jobs, new jobs, job search, scrape jobs, /scrape

Creates and runs LLM-as-judge evaluators on Arize, including managing tasks, column mappings, and continuous monitoring.